class_docstr: A deterministic model that always returns the posterior mean.
docstr: Args:
      model: The base model.
docstr_tok: ["Args",":","model",":","The","base","model","."]
code: def __init__(self, model: Model) -> None:
      r"""
      Args:
          model: The base model.
      """
      super().__init__()
      self.model = model
  
imports: from __future__ import annotations
  from abc import abstractmethod
  from typing import Callable, List, Optional, Union
  import torch
  from botorch.models.ensemble import EnsembleModel
  from botorch.models.model import Model
  from torch import Tensor
label_desc: Use image node_id 1 to create a new PosteriorMeanModel object from inherited base classes: DeterministicModel with example: obj = PosteriorMeanModel(model)